Download Detection and prognostic value of pulmonary congestion by lung

CLINICAL RESEARCH
European Heart Journal (2016) 37, 1244–1251
doi:10.1093/eurheartj/ehv745
Heart failure/cardiomyopathy
Detection and prognostic value of pulmonary
congestion by lung ultrasound in ambulatory
heart failure patients†
Elke Platz 1,2*, Eldrin F. Lewis 2,3, Hajime Uno 2,4, Julie Peck 5, Emanuele Pivetta 6,7,
Allison A. Merz 8, Dorothea Hempel 9, Christina Wilson 10, Sarah E. Frasure 1,2,
Pardeep S. Jhund 11, Susan Cheng 2,3, and Scott D. Solomon 2,3
1
Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, USA; 2Harvard Medical School, Boston, USA; 3Cardiovascular Division, Brigham and Women’s Hospital,
Boston, USA; 4Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, USA; 5Royal College of Surgeons in Ireland, Dublin, Ireland; 6Division of
Emergency Medicine and High Dependency Unit, Cancer Epidemiology Unit, Department of Medical Sciences, AOU Città della Salute e della Scienza di Torino, Torino, Italy; 7University
of Turin, Turin, Italy; 8Department of Emergency Medicine and Cardiovascular Division, Brigham and Women’s Hospital, Boston, USA; 9Department of Cardiology, Angiology and
Intensive Care, University Medical Center Mainz, Mainz, Germany; 10Department of Emergency Medicine, Massachusetts General Hospital, Boston, USA; and 11BHF Glasgow
Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
Received 12 August 2015; revised 23 October 2015; accepted 15 December 2015; online publish-ahead-of-print 26 January 2016
See page 1252 for the editorial comment on this article (doi:10.1093/eurheartj/ehw094)
Aims
Pulmonary congestion is a common and important finding in heart failure (HF). While clinical examination and chest
radiography are insensitive, lung ultrasound (LUS) is a novel technique that may detect and quantify subclinical pulmonary congestion. We sought to independently relate LUS and clinical findings to 6-month HF hospitalizations and
all-cause mortality (composite primary outcome).
.....................................................................................................................................................................................
Methods
We used LUS to examine 195 NYHA class II –IV HF patients (median age 66, 61% men, 74% white, ejection fraction
34%) during routine cardiology outpatient visits. Lung ultrasound was performed in eight chest zones with a pocket
ultrasound device (median exam duration 2 min) and analysed offline.
.....................................................................................................................................................................................
Results
In 185 patients with adequate LUS images in all zones, the sum of B-lines (vertical lines on LUS) ranged from 0 to 13. Blines, analysed by tertiles, were associated with clinical and laboratory markers of congestion. Thirty-two per cent of
patients demonstrated ≥3 B-lines on LUS, yet 81% of these patients had no findings on auscultation. During the followup period, 50 patients (27%) were hospitalized for HF or died. Patients in the third tertile (≥3 B-lines) had a four-fold
higher risk of the primary outcome (adjusted HR 4.08, 95% confidence interval, CI 1.95, 8.54; P , 0.001) compared
with those in the first tertile and spent a significantly lower number of days alive and out of the hospital (125 days
vs. 165 days; adjusted P , 0.001).
.....................................................................................................................................................................................
Conclusions
Pulmonary congestion assessed by ultrasound is prevalent in ambulatory patients with chronic HF, is associated with
other features of clinical congestion, and identifies those who have worse prognosis.
----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords
Heart failure † Pulmonary congestion † Lung ultrasound † Prognosis
Introduction
Heart failure (HF) remains an important healthcare concern
because of its high prevalence, associated morbidity, short- and
long-term mortality, and costs.1 Most HF exacerbations are related
to a progressive rise in cardiac filling pressures that precipitates
pulmonary congestion and symptomatic decompensation.2 In the
ambulatory setting, the physical examination is typically used to
evaluate pulmonary congestion in HF patients; however, auscultation is qualitative, subjective, and abnormal findings are frequently
absent in patients with chronic HF despite haemodynamic congestion.3 Since assessment of pulmonary congestion remains
* Corresponding author. Tel: +1 617 525 7932, Fax: +1 617 264 6848, Email: [email protected]
†
Institution at which work was performed: Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2016. For permissions please email: [email protected].
1245
Value of lung ultrasound in chronic heart failure patients
challenging without a gold standard, there is a critical need for quantitative markers of pulmonary congestion to increase the speed and
accuracy of diagnosis, facilitate early treatment, inform treatment titration, and potentially improve risk stratification.4
Lung ultrasound (LUS) provides a semi-quantitative assessment
of pulmonary congestion in HF that has been identified as a useful
point-of-care tool in the evaluation of undifferentiated dyspnea.5,6
‘B-lines’ are vertical lines on LUS which, when quantified, provide
a graded measure of pulmonary congestion. Although LUS has
been identified as more sensitive and specific than physical examination and chest X-ray in the acute care setting, the prognostic significance of LUS in ambulatory patients with chronic HF is unclear.5,6
Technological advances over the past two decades have made
ultrasound equipment portable with functionality and image quality
similar to high-end ultrasound systems.7 Recently, pocket size ultrasound devices have been developed by various vendors with sizes
approaching those of smart phones.
To assess the effectiveness of LUS with a pocket device in ambulatory HF patients, we related LUS measures of pulmonary congestion to clinical characteristics and 6-month outcomes in patients
with HF.
Methods
Patient population
This was a prospective, single centre, observational study in adults with
NYHA II – IV, and HF hospitalization within the past 12 months irrespective of left ventricular ejection fraction (EF). Exclusion criteria are
detailed in the Supplementary material online. Non-consecutive patients were recruited from ambulatory cardiology clinics of an academic
hospital between December 2011 and October 2014. After obtaining
informed consent, an investigator not involved in the patient’s clinical
care performed the LUS. The treating cardiology providers were
blinded to the LUS findings. This study complies with the Declaration
of Helsinki and the local institutional review committee approved the
research protocol.
Lung ultrasound imaging protocol and
analysis
Lung ultrasound examinations were performed by trained investigators
employing a standardized imaging protocol with a pocket ultrasound device (VScan, General Electric) with a phased array transducer at an imaging depth of 18 cm in sitting/semirecumbent position. Two second
ultrasound clips were recorded for each of the eight LUS zones (four
on each hemithorax) as recommended by an international guideline.8
Offline image analysis was performed on de-identified videos by two investigators (E.P., J.P.) with experience in LUS analysis who were blinded
to the clinical and outcome data. The highest number of B-lines (vertical
lines arising from the pleural line) visualized in a single intercostal space
was recorded for each zone. The sum of B-lines in all eight zones was
used for the primary analysis. Inter- and intra-rater agreement is described in the Supplementary material online.
Clinical and demographic data
Clinical and demographic data were abstracted from medical records by
a single investigator (see the Supplementary material online for definitions). A binary congestion score was computed and considered positive if any of the following was present: Crackles, jugular venous
distension (JVD), lower extremity oedema. Laboratory test results
were only reported if they were obtained within 7 days of the cardiology
clinic visit with the exception of NT-proBNP which was also reported
within 30 days of the visit. Estimated GFR (eGFR) was calculated using
the modification of diet in renal disease (MDRD) formula. Left ventricular EF was reported if the patient had a recent examination documenting
EF up to 12 months prior to the clinic visit.
Outcomes
Patients were followed for 6 months and time to first event was used for
all outcome measures. The primary endpoint was a composite of HF
hospitalization or all-cause mortality. The secondary endpoint was a
composite of urgent HF visit, HF hospitalization, or all-cause mortality.
Heart failure hospitalizations were confirmed through patient follow-up
phone calls, contacting primary care physicians/cardiologists, and review
of patients’ electronic medical records. All-cause mortality was confirmed through the institution’s electronic medical records and the social security death index. All prespecified primary and secondary
endpoints were based on standardized criteria for endpoint events in
cardiovascular trials and were adjudicated by three cardiologists
(E.F.L., P.S.J., S.C.) with extensive experience in endpoint adjudication
who were blinded to the LUS data (see Supplementary material online
for definitions).9
During the study period (May 2013), an ambulatory clinic for shortterm intravenous therapy for HF patients opened at the study site.10
Since this new treatment venue could have prevented HF hospitalizations in patients who previously would have been hospitalized, we included these urgent HF visits into a secondary composite outcome
and adjusted for the availability of this venue in all secondary outcome
analyses. A sensitivity analysis evaluating the impact of the availability of
this clinic on the primary outcome is described in the Supplementary
material online.
Statistical analyses
For the main data analysis, we divided patients into three groups on the
basis of the sum of B-lines (in tertiles) in all eight zones: Tertile 1: 0
B-lines, Tertile 2: 1 – 2 B-lines, Tertile 3: ≥3 B-lines. This approach
was chosen to assess potential trends in baseline characteristics across
tertiles with potentially lower B-line numbers than reported with highend systems.11 We assessed trends across B-line tertiles with modified
Wilcoxon rank-sum tests. Continuous variables are presented as medians (interquartile range, IQR) unless otherwise noted, and categorical
variables as counts and percentages.
Cumulative incidence functions were calculated for each of the three
groups to describe the event rate for each outcome. Cox proportional
hazard models (unadjusted and adjusted) were used to assess the effects
of B-line number (by tertile) and comorbidities on event-free survival.
Models were adjusted for potential confounding variables, including
age, sex, NYHA class, and congestion score. These covariates were chosen based on their clinical importance in relation to the outcome, using a
limited number of variables to prevent statistical overfitting.12 The direction and significance of the results remained stable when adjusting for:
days since last HF hospitalization, body mass index (BMI), and creatinine.
Harrell’s C statistic was calculated for each of the models. All models
were checked for interaction by B-line tertile. The assumption of proportionality of hazards was tested by allowing a time-varying coefficient
for the primary exposure variable (B-line tertile). In none of the models
presented was this assumption violated.
Similar unadjusted and adjusted analyses were performed using restricted mean survival time (RMST) as the response variable, where
180 days were used as the truncation time for calculating days alive
and out of the hospital for the three groups.13,14
1246
Patients in whom LUS images could not be interpreted in one or several zones (n ¼ 10) were excluded from the main analysis, but baseline
characteristics were reported. Sensitivity analyses were performed for
these patients and are described in the Supplementary material online.
The incremental diagnostic utility of B-lines in identifying subjects with
increased pulmonary or haemodynamic congestion at Day 180 was assessed comparing the physical examination findings (crackles on auscultation; congestion score) vs. LUS findings (presence vs. absence of ≥3
B-lines in eight zones) using the incremental discrimination improvement
(IDI) with 10-fold cross validation and the area under the ROC curve
(AUC) with bias corrected 95% confidence intervals (CIs).15,16 Twosided significance levels of 0.05 were used for all analyses. Data were
analysed using Stata SE, version 12.0 (StataCorp, Texas 2011).
Results
Baseline characteristics
All 200 enrolled patients underwent LUS (median duration: 2 min
per patient) and 5 patients were excluded after enrolment based
on exclusion criteria: Two patients had been previously enrolled
in our study, two were later found not to have HF as determined
by the treating cardiologist and one had pneumonia (Figure 1). Of
the remaining 195 patients, 185 (95%) had adequate LUS data in
all 8 zones and were included in the main analysis. Baseline characteristics for this cohort, stratified by tertiles of B-line number, are
presented in Table 1.
The median age of all 195 study subjects was 66 years (range
24 – 93), 61% were men, 74% Caucasian, median EF within the
past 12 months was 34% (IQR 23–51). The sum of B-lines in eight
zones ranged from 0 to 13 (median 1, IQR 0 –4).
Patients with a higher number of B-lines were more likely to be in
a higher NYHA class, have prior atrial fibrillation, cancer, less likely
to be prescribed ACE inhibitors or angiotensin receptor blockers,
E. Platz et al.
have lower sodium and haematocrit, worse renal function, and higher NT-proBNP. There was no significant difference in history of
chronic obstructive pulmonary disease (COPD) or EF across
B-line tertiles.
Baseline physical examination
Of all 195 study subjects, 17 (9%) had crackles on auscultation
(Table 2). Patients with a higher B-line number were more likely
to have a lower BMI, lower diastolic blood pressure, elevated
JVD, and more likely to have crackles on auscultation. A stratified
analysis of markers of advanced HF by BMI tertiles is presented in
the Supplementary material online.
Primary outcome
There were 50 primary outcome events during the 6-month followup time period. The unadjusted and adjusted risk of the composite
primary outcome of HF hospitalization and all-cause mortality is
shown in Table 3. The risk of the primary outcome increased with
increasing B-line number. Patients in the third tertile (≥3 B-lines)
had a four-fold higher risk (adjusted HR 4.08; 95% CI 1.95, 8.54;
P , 0.001) of the primary outcome when compared with the first
tertile. This difference was mostly driven by the increased number
of HF hospitalizations in the two higher tertiles (Table 3). After adjusting for BMI in addition to age, sex, NYHA class III/IV, and congestion score, the main results remained stable (B-line Tertile 3: HR
4.64, 95% CI: 2.09, 10.31, P , 0.001). There was no significant interaction between BMI and B-line number (P ¼ 0.166). The number of
days alive and out of the hospital (up to 180 days), as assessed by the
RMST, was significantly lower in the third tertile (125 days) when
compared with the first (165 days; adjusted P , 0.001).
Secondary outcome
There were 57 secondary outcome events (urgent HF visit, HF hospitalization, or all-cause mortality) during the follow-up period. The
unadjusted and adjusted risk of the composite secondary outcome
is shown in Table 3. Similar to the primary outcome, the risk of the
primary outcome increased with increasing B-line number. Patients
in the third tertile (≥3 B-lines) had a 3.5-fold higher risk (adjusted
HR 3.45; 95% CI 1.72, 6.93; P , 0.001) of the primary outcome
when compared with the first tertile. The composite secondary outcome was also mainly driven by the number of HF hospitalizations
(Table 3). The number of days alive and out of the hospital (up to
180 days by RMST) was significantly lower in the third tertile (121
days) when compared with the first (161 days; adjusted P , 0.001).
Sensitivity analyses for both the primary and the secondary outcome were performed including the 10 patients with incomplete
B-line data (Supplementary material online). The direction and significance of the main results remained stable.
Incremental value of lung ultrasound
Figure 1 Study flow chart. Detailing heart failure patients included in the analysis. HF, heart failure; LUS, lung ultrasound.
The incremental prognostic value of LUS when compared with auscultation as assessed by the IDI was 6.4% (95% CI 1.0, 14.4) for the
primary outcome and 4.9% (95% CI 0.6, 12.5) for the secondary outcome (see also Figure 2). Similarly, the AUC improved significantly
both for the primary (AUC delta: 0.194, 95% CI 0.147, 0.315; P ,
0.001) and the secondary outcome (AUC delta: 0.132, 95% CI
0.078, 0.213; P ¼ 0.001). The incremental prognostic value of LUS
1247
Value of lung ultrasound in chronic heart failure patients
Table 1
Baseline characteristics by B-line tertilesa (n 5 195)
Incomplete B-line
data (n 5 10)
0 B-lines
(n 5 72)
1– 2 B-lines
(n 5 54)
≥3 B-lines
(n 5 59)
P (trend)†
N/A
0
1.5 (1– 2)
5 (4– 8)
N/A
...............................................................................................................................................................................
Sum of B-line in eight zones (median, IQR)
...............................................................................................................................................................................
Demographics
Age
76 (69– 80)
61 (51–73)
64 (55–72)
73 (65– 82)
Male
6 (60)
37 (51)
33 (61)
42 (71)
White
Black
9 (90)
1 (10)
51 (71)
15 (21)
42 (78)
9 (17)
42 (71)
10 (17)
Hispanic
,0.001
0.021
...............................................................................................................................................................................
Race
0.992
0
4 (6)
3 (6)
7 (12)
Asian
NYHA class III or IV (n, %)
0
5 (50)
2 (3)
19 (27)
0
12 (22)
0
31 (53)
Days since last HF admission (n ¼ 180)
40 (9 –123)
94 (35–172)
89 (26–159)
40 (14– 161)
0.171
HF admission within past 6 months (n, %)
7 (70)
50 (70)
43 (80)
44 (75)
0.555
Hypertension
Diabetes mellitus
7 (70)
4 (40)
49 (68)
35 (49)
40 (74)
26 (48)
43 (73)
31 (53)
0.526
0.666
Atrial fibrillation
6 (60)
30 (42)
27 (50)
38 (64)
0.010
Current smoker
COPD
0
2 (20)
7 (10)
17 (24)
6 (11)
16 (30)
3 (5)
14 (24)
0.371
0.952
0.003
...............................................................................................................................................................................
Medical history
Interstitial lung disease
0
0
1 (2)
1 (2)
0.335
Obstructive sleep apnoea
PCI
3 (30)
4 (40)
23 (32)
14 (19)
12 (22)
14 (26)
11 (19)
15 (25)
0.076
0.405
CABG
7 (70)
14 (19)
14 (26)
18 (31)
0.143
Myocardial infarction
Pacemaker
6 (60)
0
16 (22)
8 (11)
14 (26)
8 (15)
18 (31)
12 (20)
0.284
0.145
CRT
3 (30)
13 (18)
9 (17)
14 (24)
0.436
ICD
Stroke
5 (50)
1 (10)
28 (39)
9 (13)
27 (50)
4 (7)
28 (48)
11 (19)
0.305
0.337
Cancer
6 (60)
11 (15)
13 (24)
18 (31)
0.038
10 (100)
6 (60)
65 (90)
54 (75)
48 (89)
38 (70)
51 (86)
33 (56)
0.495
0.022
...............................................................................................................................................................................
Medications
b-Blocker
ACE-I/ARB
Digoxin
2 (20)
12 (17)
12 (22)
15 (25)
0.218
Diuretic
Spironolactone
9 (90)
1 (10)
65 (90)
24 (33)
48 (89)
12 (22)
58 (98)
20 (34)
0.097
0.990
Calcium channel blocker
1 (10)
13 (18)
5 (9)
8 (14)
0.425
Amiodarone
Lipid-lowering drug
3 (30)
10 (100)
12 (17)
49 (68)
12 (22)
33 (61)
11 (19)
38 (64)
0.745
0.638
Aspirin/antiplatelet agent
9 (90)
48 (67)
37 (69)
33 (56)
0.222
Oral anticoagulation
8 (80)
35 (49)
30 (56)
38 (64)
0.072
Sodium (mmol/L) (n ¼ 141)
Potassium (mmol/L) (n ¼ 140)
138 (136–141)
4.0 (3.5–4.4)
139 (137– 140)
4.1 (3.8– 4.5)
138 (137–139)
3.9 (3.6–4.3)
137 (135–139)
4.1 (3.7–4.4)
0.017
0.501
Haemoglobin (g/dL) (n ¼ 76)
–
13 (11–13)
12 (11–13)
11 (10– 13)
0.052
Haematocrit (%) (n ¼ 76)
BUN (mg/dL) (n ¼ 140)
–
33 (31– 44)
38 (34–40)
23 (17–37)
37 (33–40)
29 (21–45)
34 (31– 39)
38 (27– 64)
0.041
,0.001
Creatinine (mg/dL) (n ¼ 141)
1.4 (0.9–1.8)
1.2 (0.9– 1.5)
1.4 (1.1–1.9)
1.5 (1.2–2.2)
,0.001
eGFR (mL/min/1.73 m2) (n ¼ 141)
38 (35– 72)
61 (42–76)
47 (33–63)
44 (29– 56)
...............................................................................................................................................................................
Laboratory results
0.001
Continued
1248
Table 1
E. Platz et al.
Continued
Incomplete B-line
data (n 5 10)
0 B-lines
(n 5 72)
1– 2 B-lines
(n 5 54)
≥3 B-lines
(n 5 59)
P (trend)†
...............................................................................................................................................................................
NT-proBNP (pg/mL) (+/2 7 days) (n ¼ 56)
–
1070 (239– 3017)
1986 (369–3018)
5395 (3262– 8570)
,0.001
NT-proBNP (pg/mL) (+/230 days) (n ¼ 92)
–
1095 (294– 2562)
1651 (467–4049)
5086 (3025– 9428)
,0.001
LVEF
EF (%) (n ¼ 181)
EF ≥ 45% (n, %)
46 (28–60)
36 (25– 55)
33 (22–49)
32 (23–43)
0.052
5 (50)
38 (54)
27 (58)
23 (43)
0.223
PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft; CRT, cardiac resynchronization therapy; ICD; implantable cardioverter de brillator; BUN, blood
urea nitrogen; LVEF, left ventricular ejection fraction.
a
Data are presented as median (IQR) for continuous and as count (%) for categorical data.
†
P(trend) for B-line tertile 1 –3.
Table 2
Physical exam findings by B-line tertilesa
Incomplete B-line
data (n 5 10)
0 B-lines
(n 5 72)
1–2 B-lines
(n 5 54)
≥3 B-lines
(n 5 59)
P (trend)†
...............................................................................................................................................................................
BMI (kg/m2)
a
,0.001
33 (24–37)
31 (27– 39)
29 (26–36)
26 (22– 31)
Heart rate (bpm)
Systolic blood pressure (mmHg)
71 (59–75)
125 (109–136)
75 (64– 86)
124 (113–136)
78 (65–85)
124 (110– 133)
75 (67– 83)
117 (108–130)
0.845
0.084
Diastolic blood pressure (mmHg)
69 (62–74)
74 (68– 82)
72 (65–80)
67 (61– 75)
0.001
Pulse pressure (mmHg)
Respiratory rate (breaths per min)
50 (42–61)
–
46 (40– 57)
16 (14– 18)
48 (40–62)
16 (15–18)
48 (39– 62)
16 (15– 18)
0.384
0.211
JVD (≥10 cm)
6 (60)
15 (21)
16 (30)
22 (37)
0.048
S3/4
Crackles (any)
2 (20)
0
2 (3)
1 (1)
4 (7)
5 (9)
5 (9)
11 (19)
0.175
0.001
Leg oedema (any)
6 (60)
12 (33)
18 (33)
29 (49)
0.074
Data are presented as median (IQR) for continuous and as count (%) for categorical data.
P(trend) for B-line tertile 1 –3.
†
when compared with a congestion score by the IDI was 6.6% (95%
CI: 1.9, 15.1) for the primary outcome and 5.5% (95% CI: 0.6, 15.5)
for the secondary outcome. The AUC improved both for
the primary (AUC delta: 0.136, 95% CI 0.082, 0.228; P ¼ 0.002)
and the secondary outcome (AUC delta: 0.078, 95% CI 0.024,
0.167; P ¼ 0.043).
Discussion
In this study of stable patients with NYHA class II –IV HF during an
outpatient visit, LUS measures of pulmonary congestion were associated with traditional clinical markers of congestion, regardless of
EF, but were more prevalent than auscultation findings. A higher
number of B-lines on LUS identified patients with a four-fold risk
of HF hospitalizations or death from any cause and a more than
three-fold risk of urgent HF visits, HF hospitalizations, or death
from any cause over 6 months independent of age, sex, NYHA class,
and clinical congestion score. Over 180 days, patients with the highest B-line number spent on average 40 days less alive and out of hospital compared to those with the fewest B-lines. Finally, we found
that the presence of B-lines may provide incremental prognostic
information over traditional methods of pulmonary congestion assessment in patients with chronic HF.
Prior research suggests that ambulatory patients with chronic
HF who demonstrate crackles on auscultation are at higher risk
for HF hospitalizations and death.12,17 However, auscultation findings are qualitative, subjective, and frequently absent in ambulatory
patients with chronic HF, with as few as 4% demonstrating these
findings.17 Pulmonary congestion is an important target of HF therapy and, in the outpatient setting, treatment is commonly adjusted
based on clinical signs and symptoms. In the absence of a sensitive,
specific, and quantitative gold standard for the assessment of pulmonary congestion both the clinical treatment and validation of
new methods for its assessment remain challenging. These facts
make it necessary to relate novel techniques of pulmonary congestion assessment to outcomes relevant in the population of
interest.
Association with clinical characteristics
In this study, only 19% of patients in the highest B-line tertile had
crackles on auscultation. Therefore, LUS has the potential to detect
subclinical pulmonary congestion even in a stable outpatient
1249
Value of lung ultrasound in chronic heart failure patients
Table 3
Primary and secondary outcomes and mean event free times up to 180 days
Incomplete B-line
data (n 5 10)
0 B-lines (n 5 72)
1– 2 B-lines (n 5 54)
≥3 B-lines (n 5 59)
...............................................................................................................................................................................
Primary outcome
6-month HF hospitalization
4 (40)
10 (14)
10 (19)
24 (41)
Death
Primary composite outcome
(first event)
Unadjusted HR (95% CI)
2 (20)
4 (40)
1 (1)
11 (15)
5 (9)
12 (22)
7 (12)
27 (46)
–
1
1.50 (0.66, 3.41) P ¼ 0.328
3.78 (1.88, 7.63) P,0.001
Adjusted HR* (95% CI)
–
1
1.58 (0.70, 3.59) P ¼ 0.275
4.08 (1.95, 8.54) P , 0.001
RMST* (95% CI)
–
165 days (155, 175)
156 days (143, 169)
P ¼ 0.285 (adj. P ¼ 0.173)
125 days (107, 144)
P , 0.001 (adj. P , 0.001)
...............................................................................................................................................................................
Secondary outcome
6-month urgent HF visits
1 (25)
2 (5)
3 (7)
3 (9)
Secondary composite outcome
(first event)
4 (40)
13 (18)
15 (28)
29 (49)
Unadjusted HR (95% CI)
Adjusted HR* (95% CI)
–
–
1
1
1.56 (0.74, 3.31) P ¼ 0.242
1.61 (0.75, 3.42) P ¼ 0.219
3.44 (1.79, 6.64) P , 0.001
3.45 (1.72, 6.93) P , 0.001
RMST* (95% CI)
–
161 days (149, 172)
152 days (139, 166)
P ¼ 0.346 (adj. P ¼ 0.287)
121 days (102, 139)
P , 0.001 (adj. P , 0.001)
...............................................................................................................................................................................
Censored events
VAD placement
Loss to follow-up
(for HF hospitalization)
0
2 (3)
0
0
0
3 (4)
0
1 (2)
VAD, ventricular assist device.
Primary outcome: *Unadjusted model: c-statistic 0.655. Adjusted model: covariates: age, gender, NYHA class III or IV, and congestion score (c-statistic: 0.723).
Secondary outcome: All analyses were adjusted for availability of ambulatory unit for urgent HF visits. *Unadjusted model: c-statistic 0.643. Adjusted model: covariates: age, gender,
NYHA class III or IV, and congestion score (c-statistic: 0.700).
population with known HF.18 B-lines were also associated with
other clinical and laboratory markers of congestion, including physical exam findings and, in a subset, NT-proBNP. Interestingly, patients with a higher number of B-lines also had a significantly
lower BMI, which is similar but more pronounced than in a prior
LUS study from our group in which high-end ultrasound systems
were used.18 This difference could be due to more advanced HF
in the highest B-line group with associated cachexia, a known marker of morbidity and mortality risk in this population.12 Both prior atrial fibrillation and prior cancer were more common in patients with
a higher number of B-lines in accordance with their older age. Since
patients with known primary or secondary lung or pleural cancer
were excluded, other cancer history was unlikely to impact the
number of B-lines in our study. Importantly, the prevalence of
COPD did not differ between the three groups. Lung ultrasound
could present an especially useful diagnostic tool in patients with
concomitant HF and COPD (Figure 3).
Figure 2 Percentage of patients with and without primary outcome event and findings on auscultation (crackles) vs. lung ultrasound (B-lines).
Prognostic value of lung ultrasound
There are limited data on the prognostic value of LUS in HF. Three
studies of hospitalized patients, in which study populations were either heterogeneous and not limited to those with HF, or focused on
patients with acute coronary syndrome, showed that a higher B-line
number was associated with an increased morbidity and mortality
risk in multivariable analyses.19 – 21 These studies employed high-end
ultrasound systems for the assessment of LUS findings. Only one
prior study, involving 104 HF patients, related B-lines in addition
to pleural effusions to HF hospitalization or death during a median
1250
E. Platz et al.
Figure 3 Cumulative incidence of primary and secondary outcome by B-line tertiles.
follow-up time of 1.5 years.22 The investigators found that, after
multivariable adjustment, patients with .3 B-lines in five zones or
pleural effusion(s) had an almost five-fold risk of experiencing the
primary outcome.
Similarly, in our study with a larger number of patients and events
we found that ambulatory HF patients with ≥3 B-lines in eight chest
zones are at higher risk of experiencing a HF hospitalization or dying
by 180 days. Given that only a small proportion of these patients had
findings on auscultation, the detection of subclinical pulmonary congestion has the potential to allow for earlier treatment modification
and possibly reduction of HF hospitalizations. Beyond the clinical
utility, this method could be used in trials to identify and quantify
the degree of pulmonary congestion at baseline and monitor the effect of treatment on pulmonary congestion in an objective manner.4
Incremental value of lung ultrasound
Since this technique can be either performed with a point-of-care
device or with standard high-end ultrasound equipment routinely
used in clinical practice the added cost would be low as long as ultrasound equipment is available. The average time to perform this
examination was 2 min in our study which makes integration in
standard clinical examinations even in time pressed settings feasible.
High reproducibility is another important feature of this method for
both the clinical and research arena, with a mean difference of 0.3
B-lines between readers in our study.6,23
Our findings suggest that LUS provides incremental prognostic
value when compared with both auscultation and a clinical congestion score assessed by IDI and AUC analyses. While LUS has many
advantages over auscultation, our findings should be considered hypothesis generating and will need to be investigated further in larger
trials in chronic HF populations.
outcomes. The ultrasound device employed in this study only allowed for recording of 2 s clips. Recent literature suggests that
clip length may impact the quantification of B-lines during offline image analysis.11 We thus may have underestimated the number of
B-lines in this cohort. As pocket devices with longer clip duration
have since become available, these could be utilized in future studies. Moreover, when LUS images are interpreted in real-time, clip
length would be irrelevant. In both situations, different (likely higher) cut-off values may need to be used. Although the linear trend
towards a lower BMI with increasing B-line number may be due
to more advanced HF with associated lower BMI, we cannot exclude that ultrasound device characteristics may have contributed
to the identification of fewer B-lines in obese patients. In this study,
we did not assess for the presence of pleural effusions in addition to
B-lines.22 Finally, since only a small subset of patients had natriuretic
peptides measured in proximity to their clinic visit we could not assess the incremental value of LUS over these biomarkers. However,
prior literature suggests that B-lines may provide incremental prognostic information over NT-proBNP in HF patients.22
Conclusions
Pulmonary congestion assessed by ultrasound is prevalent in
ambulatory patients with chronic HF, is associated with other features of clinical congestion, and identifies those who have a worse
prognosis. Whether LUS findings of pulmonary congestion can be
used to guide therapy and as a therapeutic target in HF deserves
consideration.
Limitations
Authors’ contributions
This was a single centre study of a well-characterized sample of ambulatory HF patients. Two HF patients met neither the NYHA class
nor the HF hospitalization criteria. However, given the substantial
event rate in our cohort, we do believe that all included patients
were at high risk of experiencing the primary and secondary
E.P., H.U.; performed statistical analysis; E.P., S.D.S. handled funding
and supervision; J.P., Em.Pi., A.A.M., D.H., C.W., S.E.F. acquired the
data; E.P.: conceived and designed the research; E.P. drafted the
manuscript; E.F.L., H.U., Em.Pi., P.S.J., S.C., S.D.S. made critical revision of the manuscript for key intellectual content.
Value of lung ultrasound in chronic heart failure patients
Supplementary material
Supplementary material is available at European Heart Journal online.
Funding
This work was supported by grants from the Eleanor and Miles Shore
Fellowship (E.P.) and the American Heart Association (grant number
13CRP14330000) (E.P.). The writing of this manuscript was supported
by a grant from the National Heart, Lung and Blood Institute (grant
number 1K23HL123533-01A1) (E.P.).
Conflict of interest: none declared.
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